5 papers
Bayesian Geostatistics Using Predictive Stacking
Lu Zhang, Wenpin Tang, Sudipto Banerjee
We develop Bayesian predictive stacking for geostatistical models, where the primary inferential objective is to provide inference on the latent spatial random field and conduct sp…
Finite Population Survey Sampling: An Unapologetic Bayesian Perspective
Sudipto Banerjee
This article attempts to offer some perspectives on Bayesian inference for finite population quantities when the units in the population are assumed to exhibit complex dependencies…
Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
Sudipto Banerjee, Xiang Chen, Ian Frankenburg +1
We develop an approach for Bayesian learning of spatiotemporal dynamical mechanistic models. Such learning consists of statistical emulation of the mechanistic system that can effi…
Leveraging national forest inventory data to estimate forest carbon density status and trends for small areas
Elliot S. Shannon, Andrew O. Finley, Paul B. May +5
National forest inventory (NFI) data are often costly to collect, which inhibits efforts to estimate parameters of interest for small spatial, temporal, or biophysical domains. Tra…
Graph-constrained Analysis for Multivariate Functional Data
Debangan Dey, Sudipto Banerjee, Martin Lindquist +1
Functional Gaussian graphical models (GGM) used for analyzing multivariate functional data customarily estimate an unknown graphical model representing the conditional relationship…